Economic Optimization Scheduling Strategy for Offshore Fishing Raft Microgrid Clusters

As a renewable energy solution for remote marine environments, marine raft microgrid clusters differ from terrestrial multi-microgrid systems and traditional single-island microgrids. In the absence of large-scale grid support, these marine raft microgrids must maintain the stability and economic efficiency of power supply within a collaborative multi-microgrid context. To address this, a multi-objective optimization approach for energy scheduling is proposed. This study initially constructs a microgrid cluster system model and introduces two economic objective functions. These functions consider both inter-microgrid power scheduling and the economic benefits of power procurement. By applying the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Constraint-based Multi-objective Evolutionary Algorithm based on Decomposition (CMOEA/D) to solve the objective functions, the results indicate that the CMOEA/D algorithm demonstrates high efficiency and accuracy in pursuing economically optimal solutions. Compared to the NSGA-II algorithm, CMOEA/D outperforms in terms of the quality of optimal solutions and iteration time, thereby enhancing the economic benefits of the microgrid cluster and validating the effectiveness of the proposed model. This research provides significant theoretical and practical guidance for energy management in remote marine environments, showcasing its profound theoretical significance and application value.